Chinese Journal of Lasers, Volume. 48, Issue 19, 1918007(2021)

LSTM-Based Recurrent Neural Network for Noise Suppression in fNIRS Neuroimaging: Network Design and Pilot Validation

Dongyuan Liu1, Yao Zhang1, Yang Liu1, Lu Bai1, Pengrui Zhang1, and Feng Gao1,2、*
Author Affiliations
  • 1College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
  • 2Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin 300072, China
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    Figures & Tables(11)
    Filtering algorithm using two-layer long-short-term-memory (LSTM)
    Input information of LSTM for classification
    Measurement paradigm in the simulative experiment
    Three-layer brain-emulating model
    Normalized time-courses of perturbed hemoglobin concentration
    Simulation results. (a) A comparison of absorption perturbation images in CC-layer at the selected time points (colorbar: 0.0001 mm-1); (b) quantitative comparison of reconstruction at the selected time points; (c) time-courses of average absorption perturbation in the activated region and the corresponding HbO and HbR concentration perturbation
    Source-detector array in the in-vivo experiment
    Measurement paradigm in the in-vivo experiment
    In-vivo experiment results. (a) A comparison of absorption perturbation images in CC-layer at the selected time points; (b) time-courses of average absorption perturbation in the activated region and the corresponding HbO and HbR concentration perturbation
    Simulation results in the presence of time delay of physiological interferences. (a) A comparison of absorption perturbation images in CC-layer at the selected time points (colorbar: 0.0001 mm-1); (b) quantitative comparison of the reconstruction at the selected time points; (c) time-courses of average absorption perturbation in the activated region and the corresponding HbO and HbR concentration perturbation
    • Table 1. Optical coefficients of brain-emulating model

      View table

      Table 1. Optical coefficients of brain-emulating model

      LayerThickness /mm(μaB, μ'sB)/mm-1
      785 nm830 nm
      Scalp5(0.0164, 0.71)(0.0191, 0.66)
      Skull7(0.0115, 0.91)(0.0136, 0.86)
      Cerebral cortex38(0.0170, 1.16)(0.0186, 1.11)
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    Dongyuan Liu, Yao Zhang, Yang Liu, Lu Bai, Pengrui Zhang, Feng Gao. LSTM-Based Recurrent Neural Network for Noise Suppression in fNIRS Neuroimaging: Network Design and Pilot Validation[J]. Chinese Journal of Lasers, 2021, 48(19): 1918007

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    Paper Information

    Received: Feb. 2, 2021

    Accepted: Mar. 29, 2021

    Published Online: Sep. 24, 2021

    The Author Email: Gao Feng (gaofeng@tju.edu.cn)

    DOI:10.3788/CJL202148.1918007

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